


'''simple docstring'''







import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

lowerCAmelCase     :  Optional[Any]											=    imread(r"""digital_image_processing/image_data/lena_small.jpg""")
lowerCAmelCase     :  List[Any]											=    cvtColor(img, COLOR_BGR2GRAY)






def       lowercase					():







       """simple docstring"""







       _lowerCAmelCase     :				str       =							cn.convert_to_negative(_A       )
       # assert negative_img array for at least one True
       assert negative_img.any()






def       lowercase					():







       """simple docstring"""







       with Image.open('digital_image_processing/image_data/lena_small.jpg'       ) as img:
              # Work around assertion for response
              assert str(cc.change_contrast(_A ,    1_1_0       )       ).startswith(
                  '<PIL.Image.Image image mode=RGB size=100x100 at'       )






def       lowercase					():







       """simple docstring"""







       _lowerCAmelCase     :				List[str]       =							canny.gen_gaussian_kernel(9 ,    sigma=1.4       )
       # Assert ambiguous array
       assert resp.all()






def       lowercase					():







       """simple docstring"""







       _lowerCAmelCase     :				List[Any]       =							imread('digital_image_processing/image_data/lena_small.jpg' ,    0       )
       # assert ambiguous array for all == True
       assert canny_img.all()
       _lowerCAmelCase     :				Optional[int]       =							canny.canny(_A       )
       # assert canny array for at least one True
       assert canny_array.any()






def       lowercase					():







       """simple docstring"""







       assert gg.gaussian_filter(_A ,    5 ,    sigma=0.9       ).all()






def       lowercase					():







       """simple docstring"""







       _lowerCAmelCase     :				Dict       =							array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]       )
       _lowerCAmelCase     :				Optional[Any]       =							conv.img_convolve(_A ,    _A       ).astype(_A       )
       assert res.any()






def       lowercase					():







       """simple docstring"""







       assert med.median_filter(_A ,    3       ).any()






def       lowercase					():







       """simple docstring"""







       _lowerCAmelCase      ,  _lowerCAmelCase     :				Any       =							sob.sobel_filter(_A       )
       assert grad.any() and theta.any()






def       lowercase					():







       """simple docstring"""







       _lowerCAmelCase     :				Union[str, Any]       =							sp.make_sepia(_A ,    2_0       )
       assert sepia.all()






def       lowercase					(_A = "digital_image_processing/image_data/lena_small.jpg"       ):







       """simple docstring"""







       _lowerCAmelCase     :				Any       =							bs.Burkes(imread(_A ,    1       ) ,    1_2_0       )
       burkes.process()
       assert burkes.output_img.any()






def       lowercase					(_A = "digital_image_processing/image_data/lena_small.jpg" ,    ):







       """simple docstring"""







       _lowerCAmelCase     :				int       =							rs.NearestNeighbour(imread(_A ,    1       ) ,    4_0_0 ,    2_0_0       )
       nn.process()
       assert nn.output.any()






def       lowercase					():







       """simple docstring"""







       _lowerCAmelCase     :				str       =							'digital_image_processing/image_data/lena.jpg'

       # Reading the image and converting it to grayscale.
       _lowerCAmelCase     :				str       =							imread(_A ,    0       )

       # Test for get_neighbors_pixel function() return not None
       _lowerCAmelCase     :				List[str]       =							0
       _lowerCAmelCase     :				Union[str, Any]       =							0
       _lowerCAmelCase     :				Optional[Any]       =							image[x_coordinate][y_coordinate]

       _lowerCAmelCase     :				Optional[Any]       =							lbp.get_neighbors_pixel(
           _A ,    _A ,    _A ,    _A       )

       assert neighbors_pixels is not None

       # Test for local_binary_pattern function()
       # Create a numpy array as the same height and width of read image
       _lowerCAmelCase     :				Optional[Any]       =							np.zeros((image.shape[0], image.shape[1])       )

       # Iterating through the image and calculating the local binary pattern value
       # for each pixel.
       for i in range(0 ,    image.shape[0]       ):
              for j in range(0 ,    image.shape[1]       ):
                     _lowerCAmelCase     :				Union[str, Any]       =							lbp.local_binary_value(_A ,    _A ,    _A       )

       assert lbp_image.any()



"""simple docstring"""



import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union

import torch

from ..utils import BaseOutput


a       :						int       		=		'''scheduler_config.json'''




class 		a_    (			_UpperCAmelCase						):
    a   :					List[Any]			     =					1
    a   :					Tuple			     =					2
    a   :					Dict			     =					3
    a   :					str			     =					4
    a   :					Optional[int]			     =					5
    a   :					Any			     =					6
    a   :					int			     =					7
    a   :					Any			     =					8
    a   :					List[Any]			     =					9
    a   :					Any			     =					10
    a   :					List[str]			     =					11
    a   :					Optional[int]			     =					12
    a   :					Any			     =					13
    a   :					Dict			     =					14







@dataclass
class 		a_    (			_UpperCAmelCase						):
    a   :					torch.FloatTensor







class 		a_    :
    a   :					Dict			     =					SCHEDULER_CONFIG_NAME
    a   :					List[str]			     =					[]
    a   :					Optional[int]			     =					True







    @classmethod
    def   _snake_case       (      cls      :							List[str]  ,       __UpperCamelCase      :							Dict[str, Any] = None  ,       __UpperCamelCase      :							Optional[str] = None  ,       __UpperCamelCase      :							List[str]=False  ,       **__UpperCamelCase      :							int  ,       )		->Dict:






        '''simple docstring'''






        _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase        = cls.load_config(
            pretrained_model_name_or_path=__UpperCamelCase  ,       subfolder=__UpperCamelCase  ,       return_unused_kwargs=__UpperCamelCase  ,       return_commit_hash=__UpperCamelCase  ,       **__UpperCamelCase  ,       )
        return cls.from_config(__UpperCamelCase  ,       return_unused_kwargs=__UpperCamelCase  ,       **__UpperCamelCase  )







    def   _snake_case       (      self      :							Tuple  ,       __UpperCamelCase      :							Union[str, os.PathLike]  ,       __UpperCamelCase      :							bool = False  ,       **__UpperCamelCase      :							List[str]  )		->Any:






        '''simple docstring'''






        self.save_config(save_directory=__UpperCamelCase  ,       push_to_hub=__UpperCamelCase  ,       **__UpperCamelCase  )







    @property
    def   _snake_case       (      self      :							Optional[int]  )		->List[Any]:






        '''simple docstring'''






        return self._get_compatibles()







    @classmethod
    def   _snake_case       (      cls      :							List[str]  )		->Dict:






        '''simple docstring'''






        _UpperCAmelCase        = list(set([cls.__name__] + cls._compatibles  )  )
        _UpperCAmelCase        = importlib.import_module(__name__.split("""."""  )[0]  )
        _UpperCAmelCase        = [
            getattr(__UpperCamelCase  ,       __UpperCamelCase  ) for c in compatible_classes_str if hasattr(__UpperCamelCase  ,       __UpperCamelCase  )
        ]
        return compatible_classes